1. Field of the Invention
The present invention relates generally to sales opportunity forecasting and, more particularly, to a method of generating estimates of a sales opportunity's impact, and the collective impact of several sales opportunities.
2. Description of the Prior Art
Typically, sales representatives within an organization are called on to evaluate their current opportunities. These evaluations usually require the individuals to give estimates of the opportunities probable financial impact over time. Currently, this is done manually, with the sales representative manually entering the estimates into a spreadsheet and then generating a forecast curve and data. This consumes considerable amount of the representative's time, is inefficient, and is stressful under a deadline; additionally, the final result is not very useful because it is often inaccurate.
Manually generating sales and related forecasts is inefficient and not very useful because the sales representatives usually do not know the finer details of the opportunity. They are not privy to the many facts and assumptions that must be determined or made in order to correctly forecast an opportunity at specific points in time. However, they generally know how the forecast curve should function over time-that is they know the general shape of the curve based on how the representatives expect the results of an opportunity to come in to the organization (slow start, then ramp up; fast start, then slow down; etc). Approximate forecast curve shapes that sales representatives typically expect and use are demonstrated in FIGS. 1-15. Further, sales representatives generally know what time period the organization should expect to experience the opportunity and what the cumulative results (total revenue, margin, and/or volume) are over that period. These individuals therefore know the overall shape of the forecast curve, its cumulative total, and the time period over which the opportunity should be forecast. They know generalities, not the fine details needed to make an accurate curve.
Prior art sales forecasting methods commonly employ historical data to extrapolate future results. In essence, the prior art uses fine details to generate forecast results that mimic/follow historical trends. For example, U.S. Pat. No. 6,910,017 describes Inventory and price decision support software. It teaches deriving a unit sales relationship based on historical data that includes prices and unit sales of an item for a succession of time periods during which the item was sold.
The prior art uses data that is not generally available to sales representatives. Further, these individuals typically have subjective knowledge of how they expect an opportunity to materialize. This may be based on prior dealings with that opportunity, or based on other factors, such as personal knowledge that an opportunity may bring in sales quickly one month and more slowly another. It is this subjective component that needs to be input into a forecast model.
Thus, there remains a need for a method of generating estimates of an opportunity's impact that saves time, reduces tension in the organization's sales force, and provides more accurate forecasts more quickly to management and financial personnel. Further, there is a need for a method and system that generates various forecast curves with a predetermined shape using cumulative results distributed over a given time period.